tebetebe: routing analysis with OSM¶
tebetebe is a Python API to compile, serve, and query routable networks using the Open Source Routing Machine (OSRM) and OpenStreetMap data, and provides a framework for routing analysis using these networks.
Package Overview¶
tebetebe makes it easy to compile a custom routing Scenario by abstracting OSRM executables into a pythonic API and provides a framework for routing analysis. With the range of customization available in the .lua configuration scripts, specific, accurate and readable transportation models can be developed and analyzed.
tebetebe also simplifies the routing analysis pipeline by enabling data to be pulled live from the OSM via the Overpass API and providing various user-contributed classes which automate common routing analysis tasks, such as isochrones.
Installation¶
1. Install osrm-backend binaries¶
See the osrm-backend wiki for instructions on how to build and install from source.
Note that the osrm-backend Docker images are not supported for use with tebetebe.
2. (option 1) Install from pip¶
pip3 install tebetebe
Examples¶
Simple Scenario¶
This example uses the eSwatini GeoFabrik extract and the default walking profile to calculate a walking route between Simunye and Mbabane.
from tebetebe.profiles import foot
import tebetebe as tb
tb_env = tb.Environment(tmp_dir="./tmp/simple_scenario")
mbabane = (31.1367, -26.3054)
simunye = (31.9274, -26.2108)
## Initialize scenario using eSwatini GeoFabrik extract and default foot profile
scenario = tb_env.Scenario("./tmp/swaziland-latest.osm.pbf", foot)
## Compile and run scenario
with scenario() as api:
## Query OSRM HTTP `simple_route` service to calculate route
route = api.simple_route(simunye, mbabane)
duration = route['routes'][0]['duration'] / 60
distance = route['routes'][0]['distance'] / 1000
print("Walking from Simunye to Mbabane")
print(" Duration: {:.2f} minutes".format(duration))
print(" Distance: {:.2f} km".format(distance))
[ INFO] swaziland-latest_foot: Compiling scenario (MLD)
[WARNING] swaziland-latest_foot: Default foot profile may not be accurate for your use case
[ INFO] swaziland-latest_foot: Initializing scenario
[ INFO] swaziland-latest_foot: Ready for requests
Walking from Simunye to Mbabane
Duration: 1420.70 minutes
Distance: 118.39 km
Scenario Comparison¶
By comparing origin:destination routes between different scenarios, we gain insight about how changing a transportation scenario affects route patterns.
Here, we compare routes calculated by two different Scenarios: a “normal” walking scenario, and a “flood” scenario, to understand the impact of a flooding event on access to local schools in eSwatini. The route network is taken from the eSwatini GeoFabrik extract, and the homesteads (origins) and schools (destinations) are downloaded from the Overpass API.
The “normal” and “flood” scenarios in this case are both the default walk profile, except that the “flood” scenaro considers nodes with ford=yes
(river crossings), and ways with flood_prone=yes
to be a barrier. Check out their source in the GitHub repo
from tebetebe.analysis import ParallelScenarios, RouteComparison
import tebetebe as tb
tb_env = tb.Environment(tmp_dir="./tmp/scenario_comparison")
## Get route network from GeoFabrik extract and POIs from Overpass API
## Load the route origins (homesteads) and dests (schools) 8km around river crossing
crossing_node_id =<PHONE_NUMBER>
highways = tb_env.OSMDataset("./tmp/swaziland-latest.osm.pbf", name="swazi")
homesteads = tb_env.POIDataset.from_overpass("""node({})->.crossing;
( way(around.crossing:8000)["building"];);
out center;""".format(crossing_node_id),
name="homesteads")
schools = tb_env.POIDataset.from_overpass("""node({})->.crossing;
( way(around.crossing:8000)["amenity"="school"];);
out center;""".format(crossing_node_id),
name="schools")
## Normal & Flood scenarios. Pass along an extra parameter to osrm-routed
## so that the max duration table size is enough for all origin:dest pairs
routed_args = {"max_table_size": len(homesteads) * len(schools) + 1}
normal = tb_env.Scenario(highways, "./profiles/walk_normal.lua",
routed_args=routed_args, name="normal")
flood = tb_env.Scenario(highways, "./profiles/walk_flood.lua",
routed_args=routed_args, name="flood")
## Run normal and flood scenarios in parallel
parallel_scenarios = ParallelScenarios(normal, flood)
with parallel_scenarios as scenarios:
## Compare origin:dest routes
comparison = RouteComparison(origins=homesteads, dests=schools)
## Routes that are different between scenarios
flood_affected = comparison.get_difference(normal, flood)
## Point dataframe of all homesteads who are flood affected
homesteads[homesteads.index.isin(flood_affected['origin_id'].unique())] \
.to_file(tb_env.tmp_dir / "flood_affected_homesteads.geojson", driver="GeoJSON")
## Routes of all flood affected homesteads under normal conditions
comparison.get_routes(normal, od_pairs=flood_affected) \
.to_file(tb_env.tmp_dir / "flood_affected_normal_routes.geojson", driver="GeoJSON")
## Routes of all flood affected homesteads under flood conditions
comparison.get_routes(flood, od_pairs=flood_affected) \
.to_file(tb_env.tmp_dir / "flood_affected_flood_routes.geojson", driver="GeoJSON")
[ INFO] Downloading POIDataset homesteads
[ INFO] Downloading POIDataset schools
[ INFO] normal: Compiling scenario (MLD)
[ INFO] normal: Initializing scenario
[ INFO] normal: Ready for requests
[ INFO] flood: Compiling scenario (MLD)
[ INFO] flood: Initializing scenario
[ INFO] flood: Ready for requests
Access Isochrones¶
Here a route network is extracted from the eSwatini GeoFabrik extract and an AccessIsochrone is calculated using the default car profile. The AccessIsochrone class is provided by the python-osrm package.
from tebetebe.analysis import AccessIsochrone
from tebetebe.profiles import car
import tebetebe as tb
tb_env = tb.Environment(tmp_dir="./tmp/access_isochrones")
mbabane = (31.1367, -26.3054)
## Initialize scenario with GeoFabrik extract and default car profile
scenario = tb_env.Scenario("./tmp/swaziland-latest.osm.pbf", car)
## Compile and run scenario
with scenario() as api:
isochrone = AccessIsochrone(api, mbabane, points_grid=1000, size=0.2)
contours = isochrone.render_contour(10)
## Save contours as GeoJSON for visualization with QGIS
contours.to_file(tb_env.tmp_dir / "contour10.geojson", driver="GeoJSON")
[ INFO] swaziland-latest_car: Compiling scenario (MLD)
[WARNING] swaziland-latest_car: Default car profile may not be accurate for your use case
[ INFO] swaziland-latest_car: Initializing scenario
[ INFO] swaziland-latest_car: Ready for requests
API Documentation¶
tb.Scenario¶
-
class
tebetebe.Scenario.
Scenario
(osm_dataset, routing_profile, name=None, algorithm='MLD', tmp_dir=PosixPath('/tmp'), overwrite=False, verbose=False, **kwargs)[source]¶ Bases:
object
Scenario is an abstraction of OSRM executables in order to compile, serve, and query a routable network.
A Scenario is initialized with (1) an OSM Dataset and (2) a Routing Profile. When called, Scenario compiles the OSMDataset and RoutingProfile into an OSRM routable network, provides a context manager to serve the scenario’s HTTP API, and returns various methods to query that API.
The HTTP API methods (match, nearest, simple_route, table, trip) are provided by the python-osrm module (https://github.com/ustroetz/python-osrm)
Example
>>> from tebetebe.profiles import foot >>> import tebetebe as tb >>> >>> ## initialize scenario with GeoFabrik extract & default foot profile >>> scenario = tb.Scenario("./swaziland-latest.osm.pbf", foot) >>> >>> with scenario() as api: ## compile scenario and serve HTTP API >>> api.simple_route()... ## query HTTP API for a simple route, match, nearest, trip...
- Parameters
osm_dataset (str / OSMDataset) – OSM dataset from which the route network will be extracted
routing_profile (str / RoutingProfile) – Routing profile to be used in scenario
name (str, optional) – Scenario name used in output file and log entries. If not supplied, it will be built based upon the OSMDataset and RoutingProfile names
algorithm (str, optional) – Algorithm to be used (either “CH” or “MLD”)
tmp_dir (str, optional) – Temporary directory to store files generated by osrm binaries
overwrite (bool, optional) – Overwrite scenario if .osrm* files already exist. Otherwise, the existing .osrm* files will be used.
verbose (bool, optional) – Print output of OSRM compilation
**kwargs – To pass any custom arguments to the OSRM executables (“osrm-routed”, “osrm-contract”, …) pass the kwarg “{executable}_args” (ex. “routed_args”, “contract_args”, …) with a dictionary of key:values to be passed
-
match
(steps=False, overview='simplified', geometry='polyline', timestamps=None, radius=None, annotations='false', gaps='split', tidy=False, waypoints=None, url_config=http://localhost:5000/*/v1/driving)¶ Function wrapping OSRM ‘match’ function, returning the reponse in JSON
- Parameters
points (list of tuple/list of point) – A sequence of points as (x ,y) where x is longitude and y is latitude.
steps (bool, optional) – Default is False.
overview (str, optional) – Query for the geometry overview, either “simplified”, “full” or “false” (Default: “simplified”)
geometry (str, optional) – Format in which decode the geometry, either “polyline” (ie. not decoded), “geojson”, “WKT” or “WKB” (default: “polyline”).
timestamps (list of timestamp, optional) –
radius (list of float, optional) –
annotations (bool, optional) –
gaps (str, optional) –
tidy (bool, optional) –
waypoints (list of tuple/list of point, optional) –
url_config (osrm.RequestConfig, optional) – Parameters regarding the host, version and profile to use
- Returns
The response from the osrm instance, parsed as a dict
- Return type
dict
-
nearest
(number=1, url_config=http://localhost:5000/*/v1/driving)¶ Useless function wrapping OSRM ‘nearest’ function, returning the reponse in JSON
- Parameters
coord (list/tuple of two floats) – (x ,y) where x is longitude and y is latitude
number (int, optional) –
url_config (osrm.RequestConfig, optional) – Parameters regarding the host, version and profile to use
- Returns
result – The response from the osrm instance, parsed as a dict
- Return type
dict
-
simple_route
(coord_dest, coord_intermediate=None, alternatives=False, steps=False, output='full', geometry='polyline', overview='simplified', annotations='true', continue_straight='default', url_config=http://localhost:5000/*/v1/driving, send_as_polyline=True)¶ Function wrapping OSRM ‘viaroute’ function and returning the JSON reponse with the route_geometry decoded (in WKT or WKB) if needed.
- Parameters
coord_origin (list/tuple of two floats) – (x ,y) where x is longitude and y is latitude
coord_dest (list/tuple of two floats) – (x ,y) where x is longitude and y is latitude
coord_intermediate (list of 2-floats list/tuple) – [(x ,y), (x, y), …] where x is longitude and y is latitude
alternatives (bool, optional) – Query (and resolve geometry if asked) for alternatives routes (default: False)
output (str, optional) – Define the type of output (full response or only route(s)), default : “full”.
geometry (str, optional) – Format in which decode the geometry, either “polyline” (ie. not decoded), “geojson”, “WKT” or “WKB” (default: “polyline”).
annotations (str, optional) –
continue_straight (str, optional) –
overview (str, optional) – Query for the geometry overview, either “simplified”, “full” or “false” (Default: “simplified”)
url_config (osrm.RequestConfig, optional) – Parameters regarding the host, version and profile to use
- Returns
result – The result, parsed as a dict, with the geometry decoded in the format defined in geometry.
- Return type
dict
-
table
(coords_dest=None, ids_origin=None, ids_dest=None, output='np', minutes=False, annotations='duration', url_config=http://localhost:5000/*/v1/driving, send_as_polyline=True)¶ Function wrapping OSRM ‘table’ function in order to get a matrix of time distance as a numpy array or as a DataFrame
- Parameters
coords_src (list) –
- A list of coord as (longitude, latitude) , like :
- list_coords = [(21.3224, 45.2358),
(21.3856, 42.0094), (20.9574, 41.5286)] (coords have to be float)
coords_dest (list, optional) –
- A list of coord as (longitude, latitude) , like :
- list_coords = [(21.3224, 45.2358),
(21.3856, 42.0094), (20.9574, 41.5286)] (coords have to be float)
ids_origin (list, optional) – A list of name/id to use to label the source axis of the result DataFrame (default: None).
ids_dest (list, optional) – A list of name/id to use to label the destination axis of the result DataFrame (default: None).
output (str, optional) –
- The type of annotated matrice to return (DataFrame or numpy array)
’raw’ for the (parsed) json response from OSRM ‘pandas’, ‘df’ or ‘DataFrame’ for a DataFrame ‘numpy’, ‘array’ or ‘np’ for a numpy array (default is “np”)
annotations (str, optional) – Either ‘duration’ (default) or ‘distance’
url_config (osrm.RequestConfig, optional) – Parameters regarding the host, version and profile to use
- Returns
- if output==’raw’ (a dict, the parsed json response.)
- if output==’np’ (a numpy.ndarray containing the time in minutes,) – a list of snapped origin coordinates, a list of snapped destination coordinates.
- if output==’pandas’ (a labeled DataFrame containing the time matrix in minutes,) – a list of snapped origin coordinates, a list of snapped destination coordinates.
-
trip
(steps=False, output='full', geometry='polyline', overview='simplified', roundtrip=True, source='any', destination='any', annotations='false', url_config=http://localhost:5000/*/v1/driving, send_as_polyline=True)¶ Function wrapping OSRM ‘trip’ function and returning the JSON reponse with the route_geometry decoded (in WKT or WKB) if needed.
- Parameters
coord_origin (list/tuple of two floats) – (x ,y) where x is longitude and y is latitude
steps (bool, default False) –
output (str, default 'full') – Define the type of output (full response or only route(s))
geometry (str, optional) – Format in which decode the geometry, either “polyline” (ie. not decoded), “geojson”, “WKT” or “WKB” (default: “polyline”).
overview (str, optional) – Query for the geometry overview, either “simplified”, “full” or “false” (Default: “simplified”)
roundtrip (bool, optional) –
source (str, optional) –
destination (str, optional) –
annotations (str, optional) –
url_config (osrm.RequestConfig, optional) – Parameters regarding the host, version and profile to use
- Returns
- if ‘only_index’ (a dict containing respective indexes) – of trips and waypoints
- if ‘raw’ (the original json returned by OSRM)
- if ‘WKT’ (the json returned by OSRM with the ‘route_geometry’ converted) – in WKT format
- if ‘WKB’ (the json returned by OSRM with the ‘route_geometry’ converted) – in WKB format
tb.OSMDataset¶
-
class
tebetebe.OSMDataset.
OSMDataset
(osm_path, name=None, **kwargs)[source]¶ Bases:
object
OSM data file from which a route network will be extracted
- Parameters
osm_path – Path to *.osm{.pbf} dataset
name (str, optional) – Name of OSMDataset. If not provided, the .osm filename is used.
-
classmethod
from_overpass
(query, name=None, overwrite=False, tmp_dir=PosixPath('/tmp'), **kwargs)[source]¶ Initialize an OSMDataset by downloading result of an overpass query and saving as .osm
- Parameters
query (str) – Query to be sent to overpass API. This query should not include an out directive (eg. [out:xml];)
name (str) – Name of the route network
overwrite (bool) – Overwrite route network if it already exists on disk
tmp_dir (str) – Temporary directory to save route network
- Returns
- Return type
tb.RoutingProfile¶
-
class
tebetebe.RoutingProfile.
RoutingProfile
(lua_path, name=None, default=False, **kwargs)[source]¶ Bases:
object
A RoutingProfile is a configuration script which represents a routing behaviour, such as for bike or car routing. It describes whether or not to traverse a particular type of way or node in OSM data, and the speed at which those elements are traversed.
Check out the osrm-backend wiki for more information! https://github.com/Project-OSRM/osrm-backend/wiki/Profiles
- Parameters
lua_path (str) – Path to .lua configuration script
name (str, optional) – Name of routing profile. If not provided, the .lua filename is used.
default (bool, optional) – If RoutingProfile is a default profile
tb.POIDataset¶
-
class
tebetebe.POIDataset.
POIDataset
(*args, name=None, **kwargs)[source]¶ Bases:
geopandas.geodataframe.GeoDataFrame
Extension of a GeoDataFrame which stores Points only, to be used as origin, destination, and waypoints in routing.
- Parameters
name (str) – Name of POIDataset (required)
-
classmethod
from_features
(features, name=None, **kwargs)[source]¶ Initialize POIDataset from GeoJSON features
-
classmethod
from_file
(path, name=None, **kwargs)[source]¶ Initialize POIDataset from file. If no name is given, the filename will be used
-
classmethod
from_overpass
(query, name=None, overwrite=False, tmp_dir=PosixPath('/tmp'), **kwargs)[source]¶ Initialize POIDataset from Overpass API query. Any returned nodes or closed ways with center attributes will be included in the dataset.
- Parameters
query (str) – Query to be sent to overpass API. This query should not include an out directive (eg. [out:json];)
name (str) – Name of the POI dataset
overwrite (bool) – Overwrite POIDataset if it already exists on disk
tmp_dir (str) – Temporary directory to save POIDataset
tb.Environment¶
-
class
tebetebe.Environment.
Environment
(**kwargs)[source]¶ Bases:
object
Environment is a convenience class to set default options for the tebetebe base classes.
Many of the tebetebe operations require writing a file to disk in order to be passed to the OSRM executables, and it’s useful to set a uniform tmp_dir for a particular set of commands so that all of these files generated by those commands are contained in the same place.
In addition to tmp_dir, any **kwarg passed to Environment will be passed to all of the classes available under the Environment. Useful examples of these kwargs include verbose and overwrite
Any **kwargs set in Environment classes will be overridden if the argument is specified during subclass initialization.
- Parameters
**kwargs – Arbitrary keyword arguments to be passed to each class available under the Environment
tb.OSRM¶
-
class
tebetebe.OSRM.
OSRM
(verbose=False)[source]¶ Bases:
object
Base class wrapper around all the osrm-* binaries. All functions accept additional **kwargs to be passed upon execution. This class is used in the background and need not be initialized directly.
- Parameters
verbose (bool) – Output stdout from osrm commands.
-
extract
(osm_path, profile_path, **kwargs)[source]¶ Call osrm-extract with a path to the osm route network and lua profile.
-
routed
(osrm_file, ready_callback, done_callback, verbose=False, **kwargs)[source]¶ Call osrm-routed on a .osrm file
- Parameters
osrm_file (str) – Path to *.osrm
ready_callback (function) – Function to be called when osrm-routed is ready for HTTP requests
done_callback (function) – Function to be called when osrm-routed has exited
verbose (bool) – osrm-routed output is so verbose it is default off even if the parent class verbose=True. Set this to true if you want to see osrm-routed output anyway.
**kwargs – Any additional parameters to be passed to osrm-routed
Analysis Plugins¶
Analysis plugins are classes written on top of the tebetebe base classes to automate routing analysis
tb.analysis.AccessIsochrone¶
-
class
tebetebe.analysis.AccessIsochrone.
AccessIsochrone
(scenario, point_origin, points_grid=500, size=0.4)[source]¶ Bases:
osrm.extra.AccessIsochrone
Compute an access isochrone from an origin point with a given ScenarioAPI
- Parameters
scenario (Scenario) – Scenario to be queried for access isochrone
point_origin (2-floats tuple) – The coordinates of the center point to use as (x, y).
points_grid (int) – The number of points of the underlying grid to use.
size (float) – Search radius (in wgs84 degrees)
tb.analysis.ParallelScenarios¶
-
class
tebetebe.analysis.ParallelScenarios.
ParallelScenarios
(*args)[source]¶ Bases:
object
Context manager for serving multiple scenarios in parallel. This can be useful for comparing routing analysis from multiple scenarios side by side.
- Parameters
*args – Arbitrary number of scenarios to be compiled, then executed in parallel
tb.analysis.RouteComparison¶
-
class
tebetebe.analysis.RouteComparison.
RouteComparison
(origins, dests, origins_id_col=None, dests_id_col=None, cache=True)[source]¶ Bases:
object
Compare route differences between scenarios
- Parameters
origins (POIDataset) – Points to be used as the origins in route comparison
dests (POIDataset) – Points to be used as the destinations in route comparison
origins_id_col (str, optional) – Column in origins dataset to be used as ID. Must be unique. If not specified, the index will be used
dests_id_col (str, optional) – Column in dests dataset to be used as ID. Must be unique. If not specified, the index will be used
cache (bool, optional) – Whether to cache time matrices
-
get_difference
(scenario0, scenario1)[source]¶ Get DF of origin:dest pairs whos routes differ between scenarios
-
get_duration_matrix
(scenario, melted=False)[source]¶ Calculate a duration matrix between origins and dests
- Parameters
scenario (Scenario) – Scenario to run calculate the duration matrix on
melted (bool, optional) – Whether the matrix should be returned as a matrix DF, or melted into origin_id dest_id and duration columns
- Returns
Duration Matrix DataFrame
- Return type
pd.DataFrame
-
get_duration_table
(*args)[source]¶ Get route duration table for multiple scenarios
- Parameters
*args – Arbitrary number of scenarios to run duration table
- Returns
DF of origin:dest pairs and durations for each scenario
- Return type
DataFrame
-
get_routes
(scenario, od_pairs=None)[source]¶ Get routes between origins and dests
- Parameters
scenario (Scenario) – Scenario on which the origin:dest routes will be calculated
od_pairs (pd.DataFrame, optional) – DataFrame of origin:dest pairs in two columns origin_id and dest_id for calculation. If not specified, all pairwise origin:dest routes will be calculated.
- Returns
GDF with duration, distance, and route geometry for each origin:dest pair
- Return type
GeoDataFrame


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1. How to compile
Install JDK7 or later versions, and Maven 3.2.5 or later versions. Directly download the code, and execute the following command in the code directory:
mvn clean install
2. Version release
Version number
ACTS uses a three-digit version number in the form of major, minor, and patch, for example, 1.0.1.
For more information, see https://semver.org/.
- Major version number: All versions within a major version number must be compatible with each other. They are not necessarily compatible with other major versions. However, it is best to be downward compatible.
- Minor version number: represents feature enhancement. The larger the version number, more features it has.
- Patch number: represents the BugFix version. Such versions are only used for bug fixing. The larger the version number, the more stable the application is.
Version maintenance
At most two versions can be maintained simultaneously.
For example, if the current version of the master branch code is 1.3.0
, the BugFix branch of version 1.2.x
will be maintained, but bugs in branch 1.1.x
will no longer be fixed. Therefore, a version upgrade for 1.1.x is recommended.
Release process
- The develop branches use SNAPSHOT versions, for example,
1.3.0-SNAPSHOT
. - Upon formal release, SNAPSHOT is replaced with a formal version number, for example
1.3.0
. - After the formal release, the next version is pulled, for example,
1.3.1-SNAPSHOT
.
3. Testing
Unit test
Add the unit test case to the model that you have developed. The package name of the test class is identical to that of the tested class.


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The deal will raise HK$88 billion (US$11.3 billion) before a so-called “greenshoe” over-allotment option is exercised, which could take the total to US$12.9 billion, according to the sources, who asked not to be named because the information has yet to be made public.
Alibaba had previously indicated it could raise up to US$13.4 billion if the greenshoe option is exercised.
In Hong Kong dollar terms, the pricing is symbolic because 8 implies prosperity in Chinese culture.
Alibaba did not immediately respond to a Reuters request for comment.
The price for the retail component of the deal will be finalized in Hong Kong on Wednesday and sources said institutional investors were due to be told at the same time how much stock they will be allocated.
Alibaba shares closed in New York on Tuesday at US$185.25, which was 0.35 percent higher for the session.
In the secondary listing, eight Hong Kong shares will be equal to one of Alibaba’s New York-listed American depositary shares (ADS), according to documents lodged with US regulators.
China International Capital Corporation (CICC) and Credit Suisse were the sponsors for the Hong Kong deal, which is the world’s biggest cross-border secondary listing to date, according to Dealogic.
The shares will be fully interchangeable between the New York and the Hong Kong stock exchanges.
– Contact us at<EMAIL_ADDRESS>CG


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Welcome to Toneanalyzer’s documentation!¶
Hello¶
- class ChatMessagesADT.ChatMessagesADT(messages=None)¶
Generates ChatMessages object based on list filled with Message objects.
- add_message(message)¶
Adds Message object.
- delete_message(idx)¶
Deletes a message from ChatMessagesADT.
- delete_old(save_period)¶
Deletes messages, which period has expired.
- delete_sentences(emotion)¶
Deletes sentences with specific tone in messages and returns deleted sentences
- fill_emotions()¶
Fills self.emotions.
- get_percentage(emotion)¶
Returns the percentage of the specific emotion in relation to all the messages, downloaded from the chat.
- get_sentences(emotion)¶
Returns sentences with specific tone.
- is_empty()¶
Checks if self.messages is empty
- class ChatMessagesADT.MessageADT(text='', created=None)¶
Generates Message object based on array filled with Sentence objects.
- delete_sentences(emotion)¶
Removes sentences with a given tone
- fill_sentences(text)¶
Generates Array filled with Sentence objects
- filter_sentences(emotion)¶
Returns sentences string with specified emotion or None if no sentences is found
- is_empty()¶
Checks, if message is not empty
- class ChatMessagesADT.SentenceADT(text='', emotion=None)¶
Generates Sentence object. Receives a sentence as a text attribute.
- text_tone.detect_tone(ukr_text)¶
Detects text’s tone by using IBM tine analyzer.
- text_tone.json_to_tone(json_object)¶
Receives json and returns the tone of the sentence.
- text_tone.translate_to_en(text)¶
Thanslates the data to English for tone analyzis.


COYOTE UGLY (director: David McNally; screenwriter: Gina Wendkos; cinematographer: Amir Mokri; editor: William Goldenberg; cast: Piper Perabo (Violet Sanford), Adam Garcia (Kevin O'Donnell), Maria Bello (Lil), Melanie Lynskey (Gloria), Izabella Miko (Cammie), Bridget Moynahan (Rachel), Tyra Banks (Zoe), Del Pentecos (Lou, The Bouncer), Michael Weston (Danny), John Goodman (Bill Sanford); Runtime: 94; 2000)
Reviewed by Dennis Schwartz
This is one of those films that you feel ashamed you saw. The characters appear to be not as bad as they seem, or as good as they seem--they just seem to be vapid. It is a film that has no direction or sense of what it wants to say, except to look good like commercials do and with the hope that it can be accepted as a "feel good" movie by the kind of public that will see anything in the summer as long as the film moves fast.
Everything about this film is a sham, from the repulsive bar it highlights to the inane relationship it features.
The producer who brought us this piece of schlock is the schlockmeister himself, Jerry Bruckheimer, the producer of such feeble projects as Flashdance, Top Gun, and Armageddon, who has lived up to his low standards with "Coyote Ugly."
Violet (Piper Perabo) is an aspiring songwriter from South Amboy, New Jersey, who lives with her widower dad, Bill (John Goodman). She is a wholesome girl, with no noticeable tattoos, body piercing, or drug habit. She also has a pleasing voice, except she freezes when she has to perform in public. Her mother was a singer, but didn't pursue her goal when she got married to her NJ State toll booth collector husband, and she told Violet that she always regretted not taking a chance and pursuing a musical career. Violet is the same age as her mother was when she went to the Big Apple, but changed her mind upon her husband's insistence.
After her lifetime friend Gloria (Melanie) helps her move into a shabby apartment in Chinatown, the hardship of breaking into the business hits home, as she gets rebuffed in all her efforts to get her demo tape listened to. A bartender plays a cruel joke on her when she tries to get info from him, telling her that Mr. Kevin O'Donnell (Adam Garcia) is a record producer. When she hands him her demo tape, she finds out that he's only a hamburger flipper, which is only one job among the many jobs the handsome Australian orphan needs in order to survive in this expensive city. His only noteworthy habit is collecting rare comic books. After the shaky start they get off to, he turns out to be a nice guy (he doesn't come onto her like an animal) and she slowly realizes that he's handsome and available, so this uninteresting romance predictably takes place while she forges ahead with her career plans.
Everything seems to be going wrong for Violet--but, to make matters worst, when she returns to her apartment, her place has been burglarized and ransacked. With little money left, she goes with her head down to an all-night diner and the kindly owner, feeling sorry for her, gives her a free piece of pie. She gets all enthused when she overhears the loud conversation of three supermodel types dressed like sluts and sees them wave around the wads of money they earned, and finds out that they are dancing bargirls in an East Village bar called Coyote Ugly, which features the Western look and Charlie Daniels Band type of country music, where the girls shake their asses on top of the bar and when not stomping on the bar, flirt with the sardine-like customers who are cramped together, screaming their heads off in some maddening bar scene fit for imbeciles. The girls are hired to lead the men on sexually but are not allowed to go further than that or date them.
The bar is run by the bold, blonde hussy Lil (Maria Bello), who hires her on the spot as one of the dancing bargirls clad in sexy halter tops. The other star bargirls are Rachel (Bridget Moynahan) and Cammie (Izabella Miko), who are seen dancing atop the bar-which at times is in flames, doing slick moves when mixing drinks, such as tossing glasses up into the stratosphere, and squirting a hose full of water at their too eager customers. Because of all the trickery involved, doubles for the bargirls were used.  The bouncer trying to control the sexually crazed, drunken crowd of men and women, is Lou. It seems odd to have only one enforcer in a place that is built for trouble, but then again, hardly anything about this film made sense.
The film ends on this supposedly endearing note, as Piper Perabo innocently exclaims, "What do you do when you realize all your dreams have come true?"
The film was about Violet trying to convince her boyfriend and her father that the bar job she has is not as bad it seems. By the film's end, she will make it in the musical field, lose her fear of performing in public, go out with her nice boyfriend and reconcile with her lovable dad. But, I'd like to see Violet try and convince anyone who is not brain dead that this film has a modicum of intelligence in it. An actor could only hope to come out of a film like this unscathed, that Piper Perabo does, is a credit to her, which is probably due to the innocent kindergarten teacher look she conveys. The film received a PG rating, despite its image of a bar from hell. But there are no hot sex scenes to satisy an audience it might be appealing to... . I haven't a clue who this movie will please, but it sure isn't me.
REVIEWED ON 8/10/2000 GRADE: D
Dennis Schwartz: "Ozus' World Movie Reviews"
http://www.sover.net/~ozus
<EMAIL_ADDRESS>© ALL RIGHTS RESERVED DENNIS SCHWARTZ
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rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
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belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
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Related links: index of all rec.arts.movies.reviews reviews


High performance suspension, driveshafts, rod ends & more
Drag & Street Suspension
CT Shocks
DS Shocks
Suspension Components
Rod Ends & Related
Drag & Street Suspension


Summary
Booru grabs a random image from mspabooru.org. JadeBot will respond to this command from both ==>mspa
and ==>booru
. Images will always be pulled from the 25 most recent images from that search result.
The Source link will link to the referenced source in the mspabooru.org post. Some sources will be to dead links, some sources may be NSFW; Art without a source will instead lead to the mspabooru page.
Usage
Default
==>mspa
==>booru
Without any arguments after the command, JadeBot will display a recent image from mspabooru.com.
Arguments
==>mspa your art_tags here -but_not_these
==>booru your art_tags here -but_not_these
Art by cndmnts, previously known as nenekofox
Every word you write after the initial command specifies a corresponding tag on the booru. Spaces denote seperate tags, and underscores specify tags that contain multiple words. A -tag specifies you do not want this tag to appear in the search result. You should be able to perform every tag you can on a *booru on jadebot. Please submit a bug if you cannot.
Note: These do not need to be ordered, as shown in the picture above, you can add a normal tag after a -tag. Some tags may be shortened (most character names do not need to be spelled out in full, e.g. you can just add jade
to get the same results as jade_harley
. Davepeta is a notable exception, and is only tagged as Davepetasprite^2
.) An extensive and full list of aliases can be found here.
Arguments relating to Shipping
==>mspa red_knight_district
==>booru red_knight_district
Unfortunately, many common ship names are not used on mspabooru; instead many long and complicated ship names are used. There are a few exceptions, including rosemary
for rosekan, and grimdorks
for johnrose. Some are very clever, some are very lame, almost all of them are word plays.
For a (mostly) complete list, please see this google doc.
Very few OT3s and polyships have ship names, there are exceptions like rule63_twilight_saga
for jaderosekan, and even that does not include all submitted art for the ship. Most of them will include multishipping
as well as their individual names, you will have to live with the inaccuracy unfortunately.
Banned Arguments
==>mspa incest gore
==>booru incest gore
JadeBot has a list of “banned” tags, some are for discord’s censor (you may not display nsfw content outside of nsfw marked channels.), some are personal morality judgements. These may change, grow or shrink in the future. The banlist does not currently change depending on if the channel is safe for work or not safe for work, but may in the future.
Banlist
- 3d - Lots of game screenshots. High probability to spam front page when new art is added.*
- *cest - The asterisk specifies that this is a wildcard search, almost all incest tags end in ‘cest’, and the ones that don’t are also tagged with ‘incest’.
- gore - Inappropriate for sfw channels.
- erasure - The ship tag for Dirk x Kanaya.
- vomit - Inappropriate for sfw channels.
- bondage - Inappropriate for sfw channels.
- dubcon - Inappropriate for sfw channels.
- mind_control - undertagged content, rarely appropriate for sfw channels.
- undergarments - undertagged content, rarely appropriate for safe for work channels.
- rating:questionable - Cheesecake/Beefcake style content, no privates are shown but often implies such content through cameltoes or erect nipples through clothing. Not appropriate for safe for work channels.
- rating:explicit - Explicit sexual content. Not allowed on mspabooru, but included for futureproofing reasons. Not appropriate for safe for work channels.
- deleteme - Content flagged for moderators to remove, mostly filled with art intentionally designed to be offensive or hurtful to others, as well as outright pornography. both of which make it worthy of banning.
* I am open for removing this ban, so this may be removed in the future.


Driver structure for an HID device implementing keyboard functionalities. More...
Public Attributes | |
| HIDDFunction | hidDrv |
| USB HID Functionn. More... | |
| HIDDReport * | inputReports [1] |
| Input report list. More... | |
| HIDDReport * | outputReports [1] |
| Output report list. More... | |
Driver structure for an HID device implementing keyboard functionalities.
| HIDDFunction _HIDDKeyboard::hidDrv |
USB HID Functionn.
| HIDDReport* _HIDDKeyboard::inputReports[1] |
Input report list.
| HIDDReport* _HIDDKeyboard::outputReports[1] |
Output report list.


--- layout: post title: Organize your reading with Read It Later date: 2011-03-11 17:30:41.000000000 +01:00 type: post published: true status: publish categories: - Books tags: - api - Apps - articles - blog - firefox - iphone - productivity - read it later - reading - reading list - twitter meta: _edit_last: '1' _thumbnail_id: '837' socialize_text: If you enjoyed this post, please consider leaving a comment below or subscribing to the RSS feed to have future articles delivered to your feed reader. socialize: '1,2' dsq_thread_id: '251463290' author: login: bbWebdesign email<EMAIL_ADDRESS>display_name: Bob first_name: Bob last_name: Belderbos ---
With so much info these days, one needs to organize. That's where Read It Later comes into play: save what you want to read and have easy access to it, anytime and anywhere. Read your articles text-only and even offline. In this post "the app" to use to organize your reading.
Like Dropbox, Read It Later is a cloud service that is extremely useful to sync content across devices. Typically in the evening I go through my twitter and facebook streams, find some interesting articles, but I don't have time to read them.
So you are faced with a dilemma: shall I just ignore this stuff, "favorite" them in twitter (while this is improper use of "favorites"), bookmark the links to a service called delicious (while I am not sure the article deserves to be bookmarked), copy the URLs to a text file or email the link to myself (which is the worst option)?
For me none of these options were really even close to an ideal solution. So I created a new account at Read it Later and I have a feeling I read more because I bundle the blogs and articles together and read them at specific intervals.
After you have created your account, if you have a mobile device, you probably want to install the app on it as well. For example for the iPhone you can do this here. Additionally you can configure your browser and twitter to use Read It Later.
You can add Read It Later to Firefox from this page and from the URL bar you can easily add links to your list clicking the yellow "greater than" icon:
You can also use alt +W or right-click + "Read this page later". In the App settings in Firefox Addons, there is a wide range of settings, it's broader than I thought..
Twitter for iphone lets you integrate you Read It Later account so that you can save links with one touch. Read It Later is integrated in lot of other apps. I find it particularly handy with Twitter where there is an infinity of articles. I typically scan the tweets and save some interesting articles for later reading. Read It Later is really helpful here.
-Read It Later has offline mode so no internet connection is required. You can download the articles when online and read them offline.
-Another great advantage is that you might have a better reading experience. With the text-only toggle you can read the article without distracting images and ads. It's similar to readability, another great app to help you "de-clutter" your reading.
-You can share to other networks, but you need the Pro version for that. I didn't try it so far.
-As shown above: lot of options and customizations. There is even an API to bring Read It Later to your own apps!
Are you using Read It Later, or you prefer alternatives like Instapaper? If so, why?
Or do you use something that is even better?
Let me know ..
- bookmarklets (use in Chrome)
You can subscribe in the sidebar to get a weekly (Mailchimp) Newsletter with my new blog posts. You can also follow my blog at Facebook. Feel free to leave a comment or contact me.


Blog Post No.1
Chef's Kitchen
28/12/2014
My take on the EDA experience is that it is a very well developed and holistic yet fluid learning environment. I am really interested in how the course emphasises personal development hand in hand with technical learning at the same time.
I'm really looking forward to getting invloved in such an open and dynamic learning environment as this is a novel approach for me that I feel will really suit how I learn and operate.
I was initially very impressed with everything I had learned about EDA but now having passed the first week I see that the model is even more involved and cohesive than I had originally thought. As a result I am really excited by the challenges that lie ahead. To be perfectly honest I am a little nervous about the course i.e. what's involved plus what I am to learn and improve about myself, although I feel it is a little like the nerves you feel before hopping on a rollercoaster. But in the end much like that fairground attraction I think we'll end up ecstatic, relieved and maybe even left with a little cleaning up to be done!


Notebooks
Story: ≠kasin's adventure with a leopard
≠kasin's adventure with a leopard
Title
≠kasin's adventure with a leopard
Collection
Summary
The narrator’s adventure with a Leopard. In the Katkop dialect by ≠kásin (L IV.-1. 3458-3464). Later ≠kasin's father goes to hunt springbok to feed the family, but misfires with the gun and comes home empty-handed, to be scolded by his wife.
Comments
1) p.3457v: this incident occurred when ≠kasin was a married man living with his father, 2) This story is found in Book IV-1
Contributors
Date
6 November 1873
Categories
History (personal), Custom and daily life
Keywords
personal history (of ≠kasin) , personal history (≠kasin's adventure with a leopard) , ≠kasin (Klaas Katkop) , ≠kasin (his personal history) , ≠kasin (hunts for his family) , ≠kasin (hunts with a gun) , ≠kasin (his adventure with a leopard) , ≠kasin (his relations) , ≠kasin (the names of his relations) , gun (≠kasin hunts with a) , gun (and ≠kasin's adventure with a leopard) , leopard (≠kasin's adventure with one) , names (of ≠kasin's relations) , names (and ≠kasin's adventure with a leopard)
Story Pages
3458-3464


{% extends "base_template.html" %} {% block title %} Final notes {% endblock %} {% block page_specific_stylesheet %} {% endblock %} {% block page_specific_scripts %} {% endblock %} {% block content %}
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{% if completion_code == "-1" %}
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_open_source
Chart width:
Needle value:
Extra Options:
hasNeedle:
true
false
outerNeedle:
true
false
needleColor:
needleStartValue:
needleUpdateSpeed:
arcColors:
arcDelimiters:
rangeLabel:
centralLabel:
rangeLabelFontSize:
save as image
copy as code


Back in Portland. Now to make bau filling and get munch down for bed.
11/22/2008, 9:28:54 PM
Favs: 0
Retweets: 0
link--- layout: tweet ---
Back in Portland. Now to make bau filling and get munch down for bed.
11/22/2008, 9:28:54 PM
Favs: 0
Retweets: 0
link


Constructor
new UnlockedSeedBundle(secret, appData)
You should not use this constructor directly.
Use one of:
- `UnlockedKeyBundle.newRandom(appData)`
- `UnlockedKeyBundle.fromLocked(encodedBytes)`
WARNING: see class-level note about zeroing / secrets.
Parameters:
| Name | Type | Description |
|---|---|---|
secret |
PrivSecretBuf | parseSecret(Uint8Array) |
appData |
object | appData to associate with bundle |
Members
appData :object
any app / user data to provide context for this particular seed
Type:
- object
signPubKey :string
the base64 encoded public key associated with this seed
Type:
- string
Methods
(static) fromLocked(encodedBytes) → {Array.<LockedSeedCipher>}
Extract the LockedSeedCipher list capable of decrypting
an UnlockedSeedBundle from an encrypted SeedBundle.
WARNING: see class-level note about zeroing / secrets.
Parameters:
| Name | Type | Description |
|---|---|---|
encodedBytes |
Uint8Array | encoded bytes to decode / decrypt |
Returns:
- Type
- Array.<LockedSeedCipher>
(static) newRandom(appData) → {UnlockedSeedBundle}
Construct a new completely random root seed with given app / user data.
WARNING: see class-level note about zeroing / secrets.
Parameters:
| Name | Type | Description |
|---|---|---|
appData |
object | appData to associate with bundle |
Returns:
- Type
- UnlockedSeedBundle
derive(subkeyId, appData) → {UnlockedSeedBundle}
Derive a subkey / seed from this seed bundle seed.
WARNING: see class-level note about zeroing / secrets.
Parameters:
| Name | Type | Description |
|---|---|---|
subkeyId |
number | derivation subkeyId |
appData |
object | appData to associate with subseed bundle |
Returns:
- Type
- UnlockedSeedBundle
lock(seedCipherList) → {Uint8Array}
Encrypt this seed into seed bundle bytes with given
seedCipherList - note, all seedCiphers will be zeroed.
WARNING: see class-level note about zeroing / secrets.
Parameters:
| Name | Type | Description |
|---|---|---|
seedCipherList |
Array.<SeedCipher> | list of seed ciphers to encrypt into the bundle |
Returns:
- Type
- Uint8Array
setAppData(appData)
You may change the app/user data with this function.
Parameters:
| Name | Type | Description |
|---|---|---|
appData |
object | appData to associate with bundle |
zero()
Zero out the internal secret buffers.
WARNING: see class-level note about zeroing / secrets.


Instagram - iPhone을 통해 아름다운 사진을 빠르게 공유
주변에서 일어나는 아름답고 중요한 순간을 포착해서 공유해보세요
Instagram is a fast, beautiful and fun way to share your life with friends and family.
Take a picture or video, choose a filter to transform its look and feel, then post to Instagram — it's that easy. You can even share to Facebook, Twitter, Tumblr and more. It's a new way to see the world.
참, 무료라고 말씀드렸었나요?


Prototype
The prototype is a specific historical or modern author, which served as the basis for an image in animation or cinema.


Behavior Questions
- Situation
- Task
- Action
- Result
Leadership Principles
We use our Leadership Principles every day, whether we’re discussing ideas for new projects or deciding on the best approach to solving a problem. It is just one of the things that makes Amazon peculiar.
- Customer Obsession
Leaders start with the customer and work backwards. They work vigorously to earn and keep customer trust. Although leaders pay attention to competitors, they obsess over customers. - Ownership
Leaders are owners. They think long term and don’t sacrifice long-term value for short-term results. They act on behalf of the entire company, beyond just their own team. They never say “that’s not my job.” - Invent and Simplify
Leaders expect and require innovation and invention from their teams and always find ways to simplify. They are externally aware, look for new ideas from everywhere, and are not limited by “not invented here.” As we do new things, we accept that we may be misunderstood for long periods of time. - Are Right, A Lot
Leaders are right a lot. They have strong judgment and good instincts. They seek diverse perspectives and work to disconfirm their beliefs. - Learn and Be Curious
Leaders are never done learning and always seek to improve themselves. They are curious about new possibilities and act to explore them. - Hire and Develop the Best
Leaders raise the performance bar with every hire and promotion. They recognize exceptional talent, and willingly move them throughout the organization. Leaders develop leaders and take seriously their role in coaching others. We work on behalf of our people to invent mechanisms for development like Career Choice. - Insist on the Highest Standards
Leaders have relentlessly high standards — many people may think these standards are unreasonably high. Leaders are continually raising the bar and drive their teams to deliver high quality products, services, and processes. Leaders ensure that defects do not get sent down the line and that problems are fixed so they stay fixed. - Think Big
Thinking small is a self-fulfilling prophecy. Leaders create and communicate a bold direction that inspires results. They think differently and look around corners for ways to serve customers. - Bias for Action
Speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk taking. - Frugality
Accomplish more with less. Constraints breed resourcefulness, self-sufficiency, and invention. There are no extra points for growing headcount, budget size, or fixed expense. - Earn Trust
Leaders listen attentively, speak candidly, and treat others respectfully. They are vocally self-critical, even when doing so is awkward or embarrassing. Leaders do not believe their or their team’s body odor smells of perfume. They benchmark themselves and their teams against the best. - Dive Deep
Leaders operate at all levels, stay connected to the details, audit frequently, and are skeptical when metrics and anecdote differ. No task is beneath them. - Have Backbone; Disagree and Commit
Leaders are obligated to respectfully challenge decisions when they disagree, even when doing so is uncomfortable or exhausting. Leaders have conviction and are tenacious. They do not compromise for the sake of social cohesion. Once a decision is determined, they commit wholly. - Deliver Results
Leaders focus on the key inputs for their business and deliver them with the right quality and in a timely fashion. Despite setbacks, they rise to the occasion and never settle.
Self Introduction
Tell me about yourself
I’m currently a Master’s student in Computer Science at Brandeis University, where I am focusing on Software Engineering, and I’ve took several related courses.
For example, Capstone Project for Software Engineering, which told me how to build a complete product from stratch, like database schema design, backend server implement, and frontend design, etc. By the way, I’m the Teaching Assistant for this coures right now.
Of course this is not enough for a good software engineer, so I’ve taken another course called Software Engineering for Scalability. This course focuses on the scalability problem in software engineering, and tought me how to improve a product to make it able to support millions of users. I learned a lot from this course, like database partitioning, like using Redis to cache frequently queried data and avoid unnecessary database access, also like using RabbitMQ to implement an asynchronized work queue to do some resourse intensive job.
Before that, I worked for MatrixCare as a Software Engineer Intern and I worked on a major release of an Electronic Health Record software. During the internship, I helped refactored the application architecture from Java EE model to Spring model, which inculdes code change, JDK update, and bugs fix.
Now that I’m finishing my Master’s degree, I’d love to focus on software engineering and discover the opportunity to work for Amazom AWS.
MatrixCare
America is heading toward a senior-care crisis, with an aging population that greatly outnumbers potential caregivers. But innovations in technology are helping organizations scale their services to provide better care with fewer staff. And MatrixCare is at the forefront of this innovation.
Much more than just an electronic health record (EHR), the MatrixCare platform enables active care management across the entire out-of-hospital spectrum. Our integrated clinical, revenue cycle, operational and financial solutions help organizations improve quality of care, simplify documentation and streamline business operations.
MatrixCare employees are passionate about creating ways to provide better care for our nation’s aging population, because that includes our parents, grandparents and other loved ones.
Last summer, I had an internship at MatrixCare, which is a full subsidiary by ResMed, and MatrixCare provides one stop healthcare solution.
The product I worked on is called Skilled Nursing, basically it’s an Electronic Health Record (EHR). For this product, there are two modals running at the same time: the legacy part is running on the Java EE modal, and the other part is running on the Spring modal.
As a Software Engineer Intern, I workd in a 5 person team that consists of our architect (he is also my manager), a senior engineer, a scrum master (because we are doing agile development) and two interns. The goal of our team was to update the legacy part and get rid of it.
Challenge
I have to be a fast learner. I’m not familiar with the stack at all, not to mention the legacy stack that were developed more than 10 years ago. It’s really important for me to figure out how they worked, a 3 month internship is not a long time, right?
Ask my manager for help, what documents should I read, my past experience helped a lot.
Because the most important task was to refactor the old stack to a new stack, and the old stack was used like more than 10 years ago, so of course I dont really understand them.
In order to do the work, I have to be a fast learner, because it’s important that I understand how they works.
I have to read a lot of documents of the old stack first, and when I dont understant or I cannot find a doc, I will go to my manager to collegues for help.
The refactor went pretty well, I helped updated several important stuff like database management service as well.
TODO
Transaction Mnagement
It’s a little bit hard to describe, but I’ll try my best.
Typically, the place where we used Transaction Management is inside the DAO layer.
We uses DAO to access the database, and do operations like read or write in there. In order to secure the process and have everyting running under transaction, we need the Transaction Management. And the Transaction Management was injected into the DAO through Spring.
In the legacy stack, we uses JtaTransactionManager for Transaction Management, JtaTransactionManager implements the UserTransaction interface.
In the legacy code, we used the programmatic way for the transaction, which is basically explicitly call begin, commit and rollback on the injected TransactionManager.
You see that we will call the commit or rollback method on the injected TransactionManager, this simply means that if we change the TransactionManager, the new TransactionManager should provides the same methods as well, so it should implement the same interface.
Unfortunately, the PlatformTransactionManager doesn’t implement that interface, and actually there’s no begin method at all. So in the worst case, in my manager’s expectation, we have to rewrite all those DAOs, and that’s a huge amount of work.
The good news is that, after read the document and compare the JtaTransactionManager & PlatformTransactionManager, I found out that PlatformTransactionManager indeed have methods doing similar things, even though the name of the methods are quite different.
This means that I could create a new bean that extends the PlatformTransactionManager and implement the JtaTransactionManager’s interface, so that the new bean will act just like the old one. For code inside the DAOs, wo don’t need any modificatoin at all.
PlatformTransactionManager
https://docs.spring.io/spring/docs/3.2.x/spring-framework-reference/html/transaction.html
<bean id="transactionManager" class="org.springframework.transaction.jta.JtaTransactionManager">
<constructor-arg ref="userTransaction"/>
<constructor-arg ref="jtaTransactionManager"/>
</bean>
<bean id="txManager" class="org.springframework.transaction.jta.JtaTransactionManager"/>
<bean id="txManager" class="org.springframework.jdbc.datasource.DataSourceTransactionManager">
<property name="dataSource" ref="dataSource"/>
</bean>
public interface PlatformTransactionManager {
TransactionStatus getTransaction(TransactionDefinition definition) throws TransactionException;
void commit(TransactionStatus status) throws TransactionException;
void rollback(TransactionStatus status) throws TransactionException;
}
legacy initialize with old bean, whilch is an interface it’s not only about the bean, have to change all code have the new stuff inmpement that interface
Log
J2EE stack to Spring, The Java EE interfaces incorporate JDBC for databases, JNDI for registries, JTA for exchanges, JMS for informing. https://www.educba.com/java-ee-vs-spring/
- Base 64 - Identify all places where sun.misc.Base64 encoding/decoding takes place
- JSP code no longer compiles under Tomcat
- JUnit test for xxxDAO
- Logging Framework Update and Configuration
- Review and Configure Transaction Mnagement Settings for Tomcat Profile to replace JBoss Tx Mgmt
Nano Twitter
It’s a twitter-like application that supports features like tweet, retweet, comment and like. Since it’s a scalability course, implementing cool features are not the first priority, all we want is to make the product scalable.
Timeline
We want a scalable timeline.
The most challenging part in this project, you might not believe, it’s actually the timline feature. Basically, in the home page, we want to display the timeline of a user. Timeline is all recent tweets sent from users followed by current user, sort by date.
Imagine you only followed one user, it’s simple to display the timeline, because all you need is simply display all that user’s tweets. But what if you followed 1000 users? The server have to get all recent tweets sent by that 1000 users, and merge them together. If we take the naive approach, we may first go to the User table and get that 1000 users’ id, and then go to the Tweet table use that 1000 id to get their recent tweets, and finally merge those tweets together. As you can imagine, this is a pretty expensive operation if the database gets too big. So how can we improve this?
Now here comes the trade off in software engineering, if we want speed, we can pay for the space. And the space we paied here is Redis. That is, for every single user, we cached the timeline for them. The form of the cache is the user’s id point to an array, in that array, it’s all tweets’ id that need to be displayed in the timeline. So when a user wants to checkout his timeline, all we need to do is take that array and do a batch query in the database.
Sounds good, right? But that’s not all. That’s when a user wants to checkout his timeline, there’s only read operation involved. What if a user with a million followers wants to send a new tweet?
Well, now we have the Redis timeline cache for each single, we just insert the new tweet into that million users’ Redis timeline instance. But that’s a million user, we can’t have this guy waiting there for the Redis to update. Why not make the update Redis process happen asynchronously? This is where RabbitMQ get introduced. We used RabbitMQ to implemented an asynchronous working queue. So after a user pressed the button to send a new tweet, that tweet will be stored in the database first, then it will be send to the RabbitMQ. When Redis service is idle, it will pop out a job from the queue and update the timeline cache.
MongoDB
Let’s consider the most important thing in Twitter, the tweet.
Assume we already have the user’s timeline stored in Redis, in the form of an sorted tweet_id array. Now we want to retrive all related data to display that a tweet.
If use SQL databse, first we will go the Tweet table and use the tweet_id to retrive that row, in that row, there may contains columns like user_id, content of the tweet, and likes. Clearly that’s not all about this tweet, instead of user_id, we need the username, so we have join the User table to get the username. Also, besides content and likes, there are also comments and attachement like pictures for a tweet, those are one to many relation. So we have to join the Comment table and Picture table as well to get all comments and pictures. In this simple case, there are already Tweet table, User table, Comment table and Picture table involved. The cost to join these tables are really expensive.
And that’s the cost to get a single tweet, there are hundreds or even more tweets in a user’s timeline. We don’t want a user to wait for a minute to see the timeline.
Instead, if we use NoSQL databse, in the Tweet table, or say collection, we can simply store username, tweet content, likes, comments and pictures in a nested fashion, we can put all of them together, that means no join operation needed at all. It’s clearly faster to retrive a Tweet.
This is only a simple scenario about the advantage to choose NoSQL. Also, if we want to horiziontally scale the database to have multiple database nodes running, it’s far easier to scale with a NoSQL database.
React
The reason to choose React is simple, biggest reason is that we want to learn it. Also, by using React, we can separate Frontend from Backend, so for the backend we can simply make it an API server, there’s no need to render and transmit the whole HTML to clients.
Why xxx
Amazon
Because I know Amazon is a top internet retailing company with a strong focus on customer experience. And there are a lot of talented people in amazon creating amazing products to make people’s life easier.
Actually I have a roomate work at amazon, and he always showes a strong ownership to his projects and he always wants to make things perfect. This really touches my heart and reminds me of the time when I was working on the Workout TeampUp social networking applicaiton, I spent days and nights to polish the UI simply because I want to give a perfect user experience.
I believe I have similar spirits with Amazon, that one of the biggest reason why I want to join Amazon.
Vecna
- I know it’s a self patient health care product, can you tell a bit more about this product
- how did you came up with the idea to make this non-profit?
- future plan, you have robot, what’s else
Deadline / Time management
What if you can’t make the deadline
During my internship at MatrixCare, I was once given one week to update the logging framework from log4j to log4j2. I believe I could handle this because it didn’t sound that complicate, so I accepted. But it turned out that I was not that familiar with the product and underestimated the amount of work I have to do.
When I realized that the deadline was fast approaching, I explained the situation to my manager and asked for an extension, which he granted.
Finally I met the second deadline, and I learned that I need to be honest with myself about the workload I can handle. I also learned that when accepting assignments, I need to include extra time to ensure even there is a roadblock, I can still meet the deadline.
Handle multiple task at same time
During my internship at Matrixcare, since we are following the agile development process, we have bi-weekly sprint to list tasks that we have to do in the following 2 weeks. So for myself, I have a TODO list to list all tasks assigned to me from most important to least important, and finish them one by one. Beside the TOOD list, I also uses a calendar app to help me be organized, because there are meetings, appointments, etc. With the help of TODO list and calendar, I will never missing any important events.
Mistake
Netagive feedback from teammate
- Tell me about a time when you were wrong
When I was working on the Workout TeamUp project with other two teammates, one of the teammates complained to me that I was always working alone and didn’t paying enough attention to the team.
This happened because it’s a course project, it’s new to all of us, and I have to learn how to do it. I enjoy the process to solve problems by myself, because I found it satisfying, so I rarely discuss with my teammates about any obstacles.
After the teammate’s complain, I realized that I have to make more communication with the team. so we decide to have daily short meetings to talk about any roadblocks, and share experiences with each other.
It’s only a short meeting, but we found that it clearly improved the whole team’s efficiency.
updating logging framework, go back and forth
I’m passionate about learing new stuff, but maybe I’m too passionate and sometime this lead to trouble
Cannot make the commitment
Ref to deadline
Ownership
Leaders are owners. They think long term and don’t sacrifice long-term value for short-term results. They act on behalf of the entire company, beyond just their own team. They never say “that’s not my job.”
Tell me about a time when you had to leave a task unfinished.
ref to tight deadline
- Tell me about a time when you had to work on a project with unclear responsibilities.
Insist on the Highest Standards
Leaders have relentlessly high standards — many people may think these standards are unreasonably high. Leaders are continually raising the bar and drive their teams to deliver high quality products, services, and processes. Leaders ensure that defects do not get sent down the line and that problems are fixed so they stay fixed.
Tell me about a time when [you, team member] couldn’t meet your expectations on a project.
ref to tight deadline
Customer Obsession
Leaders start with the customer and work backwards. They work vigorously to earn and keep customer trust. Although leaders pay attention to competitors, they obsess over customers.
Who was your most difficult customer?
Honestly say, I dont have a rich experience work with real “customers” yet, but since I’m doing a TA for the Capstone course, I do have a lot of experience with my student customers.
One of the most important duty for being a TA is to answer students’ questions. And once I had a student having trouble with an assignment, it’s a really hard one, and he didn’t know how to start with it. Definitely I can’t do the assignment for him, so gave him some helpful materials to look at, and suggested him with a possible approach to do it.
I emailed him the second day to see if he was still having trouble with it, and he says that my suggestion was really helpful and he finished the assignment.
- Give me an example of a time when you did not meet a client’s expectations. What happened, and how did you attempt to rectify the situation?
- When you’re working with a large number of customers, it’s tricky to deliver excellent service to them all.
Are Right, A Lot
Leaders are right a lot. They have strong judgment and good instincts. They seek diverse perspectives and work to disconfirm their beliefs.
Tell me about a time when you had to work with incomplete data or information.
TODO
fix the front end
During my internship at MatrixCare, I was given a task to fix a front-end bug caused by the update of container.
Hire and Develop the Best
Leaders raise the performance bar with every hire and promotion. They recognize exceptional talent, and willingly move them throughout the organization. Leaders develop leaders and take seriously their role in coaching others. We work on behalf of our people to invent mechanisms for development like Career Choice.
Tell me about a time when you mentored someone.
ref to difficult customer
Deliver Results
Leaders focus on the key inputs for their business and deliver them with the right quality and in a timely fashion. Despite setbacks, they rise to the occasion and never settle.
- By providing an example, tell me when you have had to handle a variety of assignments. Describe the results.
- What is the most difficult situation you have faced in your life? How did you handle it?
- Give me an example of a time when you were 75% of the way through a project, and you had to pivot strategy–how were you able to make that into a success story?
TODO
handle multiple task at a time, tight schedule
Bias for Action
Speed matters in business. Many decisions and actions are reversible and do not need extensive study. We value calculated risk taking.
- Describe a time when you saw some problems and took the initiative to correct it rather than waiting for someone else to do it.
- Tell me about a time when you took a calculated risk.
- Tell me about a time you needed to get information from someone who wasn’t very responsive. What did you do?
TODO
Dive Deep
Leaders operate at all levels, stay connected to the details, audit frequently, and are skeptical when metrics and anecdote differ. No task is beneath them.
- Give me two examples of when you did more than what was required in any job experience.
- Tell me about something that you learned recently in your role.
Invent and Simplify
Leaders expect and require innovation and invention from their teams and always find ways to simplify. They are externally aware, look for new ideas from everywhere, and are not limited by “not invented here.” As we do new things, we accept that we may be misunderstood for long periods of time.
- Tell me about a time when you gave a simple solution to a complex problem.
- Tell me about a time when you invented something.
Learn and Be Curious
Leaders are never done learning and always seek to improve themselves. They are curious about new possibilities and act to explore them.
- Tell me about a time when you influenced a change by only asking questions.
- Tell me about a time when you solved a problem through just superior knowledge or observation.
- How do you stay inspired, acquire new knowledge, or innovate in your work?
Think Big
Thinking small is a self-fulfilling prophecy. Leaders create and communicate a bold direction that inspires results. They think differently and look around corners for ways to serve customers.
- Tell me about your proudest professional achievement.
- Tell me about a time when you went way beyond the scope of the project and delivered.
Frugality
Accomplish more with less. Constraints breed resourcefulness, self-sufficiency, and invention. There are no extra points for growing headcount, budget size, or fixed expense.
- Tell me about a time when you had to work with limited time or resources.
Earn Trust
Leaders listen attentively, speak candidly, and treat others respectfully. They are vocally self-critical, even when doing so is awkward or embarrassing. Leaders do not believe their or their team’s body odor smells of perfume. They benchmark themselves and their teams against the best.
- What would you do if you found out that your closest friend at work was stealing?
- Tell me about a time when you had to tell someone a harsh truth.
- Tell me a time when you earned the trust of a group.
Have Backbone; Disagree and Commit
Leaders are obligated to respectfully challenge decisions when they disagree, even when doing so is uncomfortable or exhausting. Leaders have conviction and are tenacious. They do not compromise for the sake of social cohesion. Once a decision is determined, they commit wholly.
- Tell me about a time when you did not accept the status quo.
- Tell me about an unpopular decision of yours.
- Tell me about a time when you had to step up and disagree with a team members approach.
- If your direct manager was instructing you to do something you disagreed with, how would you handle it?


Below is an example of how a contact form might look with this template:
Name
Email Address
Message
NOTE: A contact form such as this would require some way of emailing the input to an email address.


Why are you not satisfied with consuming my flesh?
23 Oh, that my words were now written down!
Oh, that they were inscribed in a book!
24 Oh, that with an iron pen and lead
they were engraven in the rock forever!
25 But as for me, I know that my Redeemer lives,
and that at last he will stand on the earth;
26 after my skin, that is, this body, is destroyed,
then in my flesh I will see God.
27 I will see him, I myself will see him on my side;
my eyes will see him, and not as a stranger.
My kidneys fail within me.
28 If you say, 'How we will persecute him!
The root of his troubles lies in him,'
29 then be afraid of the sword,
because wrath brings the punishment of the sword,
so that you may know there is a judgment."


Ellen Physiotherapy
Ellen needed a simple yet effective single page layout to launch her business as as self employed physiotherapist in the South West London area.
She had some initial ideas so this made the design phase quite quick. The logo was done from her original ideas that I have adapted.
We have also created business cards to go with the website using the wonderful Moo luxe cards
As there was no requirement to quickly update the site, I simply used a pure ruby application using sinatra. This makes this small site very fast and as her partner, easy to update for me!


--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/type.20class.20inference.20system.html ---
Two (classes of) related questions:
1) Is there some reference for the type class inference algorithm that Lean uses? Is it ad hoc, or does it follow some established algorithm? Is it documented in some paper?
2) How will Lean 4 impact the type class system? Is it planned to remain the same, or will it go through a major revision?
Is there some reference for the type class inference algorithm that Lean uses? Is it ad hoc, or does it follow some established algorithm? Is it documented in some paper?
I think the canonical answer is that it's a λProlog interpreter, which synthesizes instances by essentially backchaining. We typically cite [1].
[1] D. Miller and G. Nadathur. Programming with Higher-Order Logic. Cambridge, 2012.
(Not entirely sure if this is helpful.)
Yes, I think it answers 1).
How will Lean 4 impact the type class system? Is it planned to remain the same, or will it go through a major revision?
I don't expect any significant changes, but Sebastian can probably speak more authoritatively on this topic.
There are no changes to the type class system planned right now
Maybe I have a newbie question 3): Are coercions and type class inferences somehow two avatars of some underlying common principle?
/me just realises that the Miller--Nadathur reference is a 300 page book...
Once Lean 4 is ready, someone should write "The Leanbook". Alas, I hear that Don Knuth's todo list is non-empty ;-)
I would love to understand the inner workings of Lean. But I'm not a very proficient source reader. In that regard I found the TeXbook very enlightening.
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


All Classes
Car
Chassis
Engine
ExteriorFeature
Feature
InteriorFeature
Main
ManufacturedEngine
Vehicle
VehicleChassis
VehicleFrame


Advocate for youth engagement determined to improve the system
The Coding Wizard and Computer Science graduate
High school student with a love of writing and volunteering
Community Developer with a passion for Volunteerism
High school student driven for change
A motivated individual who is determined to bring about
Young leader with a passion for improving health outcomes and empowering underprivileged youth
A recent engineering graduate passionate about innovation and technology


HOW STELLA GOT HER GROOVE BACK (Twentieth-Century Fox) Sitting through "How Stella Got Her Groove Back," adapted from the novel by Terry McMillan, is like listening to the private fantasies of any number of young women -- black, white, Asian, etc. -- who feel dissatisfied with their lives but too timid to make major changes. The movie, two hours of sumptuous-looking wish-fulfillment, should appeal greatly to this audience, provided they're willing to overlook some substantial problems in the material. Stella, the ostensibly grooveless heroine, is played by the stunning Angela Bassett, who couldn't look out-of-sorts even if she went without sleep for a week. Although Stella has a prime position as an investment banker, an almost eerily polite pre-teen son Quincy (Michael J. Pagan) and a magnificent San Francisco home, she's been sleeping single in a double bed for many moons. During an impromptu journey to Jamaica with her ribald best friend Delilah (Whoopi Goldberg), 40-year-old Stella slips into the arms of the improbably named Winston Shakespeare (Taye Diggs), a 20-year-old dreamboat debating over whether or not to attend medical school. This is the kind of film that has to go to great lengths to tell us Winston is very intelligent, since his behavior throughout the story suggests otherwise. Although the duo seem to have nothing in common except a penchant for making love in rooms bathed in the glorious glow of a sunset or doing it in the shower while warm water outlines their magnificently chieseled bodies, Stella finds it difficult to walk away from her casual fling, especially since she returns home to find her gossipy sisters (Regina King and Suzzanne Douglas) want to speak of nothing else. The age difference seems to shock most everyone in Stella's circle to no end, although one of the curious flaws of "Stella" is that Bassett and Diggs don't look like they're a generation removed from each other; it's not exactly Anne Bancroft and Dustin Hoffman. The Jamaica sojourn -- easily the best and most enjoyable portion of the movie -- gives way to multiple conversations and debates over the wisdom of pursuing a hot young lover. Winston eventually comes to visit Stella and ends up spending more time playing video games with Quincy than seeking out a career. When Stella and Winston go to the movies, they end up seeing what looks like a sex comedy rather than the more sophisticated entertainment she prefers, and Stella admits to Delilah Winston has been messing up the bed with, of all things, Cocoa Puffs. Is Stella robbing the cradle? Is Winston robbing the grave? Will the movie ever include a single scene that doesn't feel wholly manufactured? "Stella" comes straight from the "designer problems" school of screenwriting, a genre in which stories are built around wealthy, gorgeous people who have to create their own miseries in order for anything remotely dramatic to occur. Like designer clothes, these kinds of worries are far above the means of most of us. Stella, for example, loses her job even though she appears to be the only one in her office who ever works and she's certainly the only African-American woman in the place; can you say "instant lawsuit"? Most of us, faced with unemployment, would immediately begin a job hunt and avoid unnecessary expenses. But our gal Stella wings to Jamaica, lives it up, flies back to the islands again, jumps on a plane to New York at the drop of a hat, moves Quincy and Winston into the Waldorf, and then hires a limo to take her home from the airport. Yet she somehow finds time to fret over how she's going to make next month's mortgage payment as she and Winston dine out at an elegant-looking bistro. In the midst of so much glittering cotton candy, Bassett comes across as a pillar of strength and credibility, even if you can't imagine such a terrific woman would ever spend a night alone or waste time listening to the disapproval of friends and family. Diggs has a great smile but Winston exists primarily as a concept rather than a a character.  James Sanford
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pyedbglib.serialport¶
pyedbglib.serialport.serialcdc¶
This subclass of pyserial’s serial.Serial class is intended to work exactly like the original, with the exception that the constructor has an extra argument ‘open_timeout’ (default = 30). The open() method will do the specified number of retries to wait for a CDC serial port device to be created/accessible.
pyedbglib.serialport.serialportcheck¶
Utility for checking whether a (virtual) serial port is accessible or not.
- pyedbglib.serialport.serialportcheck.check_access(port)¶
Check if user has access to kit’s virtual serial port. In many Linux distros access requires membership of the ‘dialout’ group which is not default.
- Parameters
port – port name to check
- Returns
boolean - access is allowed
pyedbglib.serialport.serialportmap¶
Serial Port Mapper Kits like Curiosity Nano consist of a composite USB device with multiple interfaces, including a virtual serial port. The USB serial number belongs on a device level. This utility offers a mechanism for linking the virtual serial port to its parent USB device.
- class pyedbglib.serialport.serialportmap.SerialPortMap¶
Bases:
object
This is a utility to find virtual serial port name based on HID device serial number, or vice versa.
- find_hid_tool(port)¶
Find HID tool based on virtual serial port name
- Parameters
port – port name to find
- Returns
HID tool object or None
- find_matching_tools_ports(serial_endswith)¶
Find tools and ports matching (partial) serial number.
- Parameters
serial_endswith – serial number, or at least end part thereof
- Returns
List of matching {tool, port} dicts
- find_serial_number(port)¶
Find HID tool serial number based on virtual serial port name This is redundant, but added for convenience
- Parameters
port – port name
- Returns
HID tool serial number or None
- find_serial_port(serial_number)¶
Find virtual serial port based on serial number exact match
- Parameters
serial_number – serial number of tool
- Returns
Name of virtual serial port or None.
pyedbglib.serialport.wincdc¶
Class with helper functions for CDC virtual com ports on Windows. This code taken from pyatmeltcftester project and minimally adapted for python3. This code still needs to be Python2 compatible. This module should not be used directly, use SerialPortMap instead for cross-platform functionalty.
- class pyedbglib.serialport.wincdc.CDC¶
Bases:
object
Windows-only implementation of hid device to CDC serial port map.
- find_cdc_port(tool, serial)¶
Find virtual serial port name based on tool name and serial number
- Parameters
tool – tool name
serial – tool serial number
- Returns
serial port name, or None if not found
- Raises
ValueError – if input arguments are not valid
- func_name()¶
Get function name
- iter_keys(key)¶
Iterate over subkeys of a key
- iter_keys_as_str(key)¶
Iterate over subkeys of a key returning subkey as string
- iter_vals(key)¶
Iterate over values of a key


Bookmarks Menu
Autres favoris
ML books
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems (English Edition) eBook: Géron, Aurélien: Amazon.fr
- faculty.neu.edu.cn/yury/AAI/Textbook/Deep Learning with Python.pdf
- GitHub - ageron/handson-ml2: A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
- Deep Learning with Keras [Book]


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Adult literacy in Ipswich is set to get a boost as a national initiative arrives in the town at the end of January.
Read Easy UK is a national charitable organisation which trains local groups of volunteers to provide free coaching to help adults build their reading skills, confidence and self-esteem. Read Easy Ipswich is looking for volunteers to provide confidential, one-to-one support for anyone over the age of 18 who can’t read or struggles with reading. They should be able to read fluently and willing to spend time on a regular basis teaching someone else to read.
Anyone interested in finding out more or getting involved with Read Easy Ipswich is invited to a public meeting on Wednesday 31 January. The event, organised by local literary project Let’s Talk Reading, will take place at the University of Suffolk Waterfront Building in Ipswich from 4:30pm - 6pm. If you are interested in attending the launch event or getting involved in Read Easy Ipswich, call 07736 579963 or email<EMAIL_ADDRESS>Sessions would usually be in a discreet and convenient place, so Let’s Talk Reading are also looking for any offers of suitable venues.
There is a significant need for this help in Ipswich. 7% of adults in England have serious reading difficulties and as many as 1 in 6 struggle with reading. England’s 16-24 year-olds came 22nd out of 24 developed countries for literacy in an OECD report in 2013.
Adults with reading issues can feel very isolated and find that it adversely affects their social mobility. They often hide their problems and may feel embarrassed to join a class, so one-to-one, confidential volunteer support can be a real lifeline.
John Helleur, co-founder of the Let’s Talk Reading project, said:
“Like all parts of the country, Ipswich has a large number of people who struggle with reading, which makes their lives very difficult and often means that they are unable to find employment. They will normally hide this lack of skill, but we feel that everyone has the ‘Right to Read’.
“Our partnership with Read Easy is one key piece in a set of solutions which we are establishing in Ipswich, and which we hope will eventually enable everyone in the town to read more confidently to help them cope with modern life. With Read Easy we will establish a team of volunteer coaches to work with individual adults each week until they can read. This will be entirely free, and done in confidence somewhere local to the student, where they can feel comfortable learning.
“We are working to set up four main areas for coaching, in SE, NW and SW Ipswich, plus building on the work of our other partner, local charity Got to Read, in the centre of town. If any fluent readers are keen to help with this vital work in the community, please let us know, or come to our public meeting on the 31st January.”
Ginny Williams-Ellis, CEO of Read Easy UK, said: “Read Easy is absolutely delighted to be partnering with Let’s Talk Reading in Ipswich in order to support adults with their reading. We are really impressed by the work already being done. It will be great to see a new Read Easy group being set up as part of it.”
Alison Wheeler, chief executive of Suffolk Libraries, said: “Suffolk Libraries are very pleased this initiative is coming to Ipswich and I’m personally especially keen to support anything which helps people to be more confident as readers as it affects so many aspects of everyone’s life.”
Read Easy is already working in 23 other places around the country, including Cambridge.


As students of psychology, we are accustomed to poring through journal articles and course-approved textbooks to stay up-to-date on the latest developments in the field. While these resources are the cornerstones of scientific research, there are myriad other ways to enhance our understanding of our chosen disciplines – namely through podcasts!
Although a relatively new arrival to the field of science, podcasts have been wholly embraced by the scientific community with many major journals such as Nature, Cell and PNAS, featuring podcast programmes tailored to interested members of the community. One of the reasons that podcasts are so successful is that they offer an alternative portal to the scientific world. Not only do they document and discuss current research findings by visiting labs and reporting from the field, but they also take the listener behind-the-scenes by interviewing leading scientific experts who work in a wide range of disciplines.
Furthermore, podcasts are particularly beneficial to aspiring researchers and clinicians as they cover a wide breadth of pertinent topics, which are communicated in a manner that is accessible to students.
We at JEPS have compiled a list of our favourite podcasts, for those of you who are interested in boosting your brains via a lively and enjoyable medium. The podcasts detailed below are suitable for both undergraduate and graduate students of psychology and neuroscience. In addition, each of these podcasts can be downloaded from the podcasts app on IOS and android devices or directly from the websites (all of which are listed below).
Radiolab
Radiolab is hosted by Jad Abumrad and Robert Krulwich and it is produced by WNYC. The show focusses on topics that are predominantly scientific and philosophical in nature, thus it is an enticing option for both students of psychology and neuroscience. What differentiates this podcast from many others is its distinctive production style. Interviews are interspersed with stories, thought experiments, and original music such that listeners of all ages and backgrounds remain engaged from start to finish. The programme succeeds in communicating often complicated and ambitious topics to a global audience, which makes it an ideal starting point for anyone looking for a smooth transition into the thought-provoking world of podcasts.
Sample Episodes:
Episode Length: Full Episodes (One Hour); Shorts (15 - 30 minutes)
Brain Science
The Brain Science Podcast is hosted by Ginger Campbell MD. During this time, the host interviews a leading expert about their work in a brain-related field, with topics ranging from brain plasticity, chemistry, imaging and cell biology to developmental and neurodegenerative disorders. This immersive and informative podcast caters for listeners of all backgrounds by summarising key ideas in the field as well as sharing recent discoveries from neuroscience research.
Sample episodes:
- Brain Anatomy Revealed
- Exercise promotes Brain Plasticity
- The Autistic Brain
- How do you feel?
- What do Mirror Neurons Do?
Episode Length: 40 minutes to one hour
Philosophy Bites
Philosophy Bites is hosted and produced by philosophers David Edmonds and Nigel Warburton. As students of psychology, we often become fixated on a particular research topic, which exists in a highly specialised field of study. While we may believe that other methods and disciplines are irrelevant to our particular research goals, this could not be further from the truth. It is for this reason that Philosophy Bites is essential listening for all students of psychology. This podcast highlights the importance of philosophical thinking for current day psychological research. In many ways, the topics discussed by the hosts provide an overarching context for the objectives and goals harboured by modern-day psychology.
Sample episodes:
- Ted Honderich on What it is to be Conscious
- Simon Blackburn on Narcissism
- Cassim Quassam on Conspiracy Theories
- Shelly Kagan on Speciesism
- Williamson on the Appeal of Relativism
Episode Length: 15 - 25 minutes (approximately)
Naked Neuroscience Enhanced
Naked Neuroscience Enhanced is a strand of the popular Cambridge University and BBC radio show Naked Scientists, hosted by Hannah Critchlow, PhD. The aim of this podcast is to disseminate neuroscience research findings in an engaging and lively manner to a global public audience. This podcast is highly interactive, which makes it invaluable to undergraduate students who are interested in better understanding how the brain and nervous system work. Often recorded on the road, the listeners are transported to all corners of the globe, from a brain bank in New Zealand to a yogic laughter clinic in Cambridge.
Sample Episodes
- Tickling your Brain: Why Do We Laugh?
- Paying Attention to ADHD
- How to Nurture a Child’s Brain
- Morality and Motivation
- Is Technology Tweaking our Brains?
Episode Length: 30 minutes (on average)
Brain Matters
The Brain Matters Podcast is hosted by Matt Davis and Anthony Lacagnina. This podcast is suitable for both undergraduate and graduate students, however as the topics are quite specialized, they may be of more interest to graduate students of neuroscience. What differentiates this podcast from both Brain Science and Naked Neuroscience Enhanced is that this program is hosted and produced by graduate students at the University of Texas at Austin. This angle is particularly beneficial to students as the hosts place a considerable emphasis on discussing the career trajectory of the interviewee, which provides a valuable insight into the challenges and rewards of life as a research scientist.
Sample episodes:
- Decisions in the Brain with Dr. Nao Uchida
- Discovering Circuits with Dr. Massimo Scanziani
- Alcohol and the Fetal Brain with Dr. Rajesh Miranda
- Making the Most of Memory with Dr. Wendy Suzuki
- What Can you Remember? With Dr. Anthony Wagner
Episode Length: 40 minutes (on average)
All in the Mind
All in the Mind is hosted by psychologist Claudia Hammond and produced by the BBC. The aim of this podcast is to communicate psychological research to a global audience on current research in the field. Similar to the neuroscience-focused podcasts, All in the Mind features interviews with many leading researchers on topics ranging from mental health policies and media portrayals of mental health to body dysmorphic disorder and perinatal obsessive compulsive disorder. Although this podcast would be engaging for both undergraduate and graduate students of psychology and neuroscience, it would particularly appeal to students with an interest in clinical, counselling and health psychology.
Sample episodes:
- Money and Motivation; Street Therapy and Insanity Law
- Taxi Drivers; Mental Illness and Work; Neuroscience and the Law
- Romanian Orphanage Babies: 21 Years On
- Psychology of Voting; Media Portrayals of Mental Health; Designer Asylum
- Ageless Psychiatry; From DNA to the Brain; Recipe of Life
Episode Length: 28 minutes (exactly)
Are there any other podcasts that we forgot to include and that you think deserve a mention? Please include any suggestions in the comments!


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